The relationship between student employment, employability-building activities and graduate outcomes

ABSTRACT

There is continued pressure on universities to develop future-oriented graduates given documented skill gaps and global talent shortages. Although work experience supports work-readiness and is prioritised among graduate employers, little is known about the labour market gains from student employment compared to work experience embedded within the curriculum (e.g. internship or work placement), and how one may influence the other. Drawing on the lens of capital resources and signalling theory, this study uses national survey data from 152,226 recent Australian graduates to examine the relationship between student employment, in-curricular work experience and labour market outcomes. The findings affirm the high incidence of student employment and distinctions in labour market effects by type of work undertaken during study. Student employment influenced participation in embedded work experience and other employability-building activities facilitated by universities. Taking part in in-curricular work experience led to clear labour market gains, irrespective of the type of employment students engaged in during their university years. This paper discusses important implications for universities striving to develop student employability and achieve more uniform graduate employment outcomes among diverse cohorts.

KEYWORDS:

• Employability
• student employment
• extra-curricular activities
• signalling
• capital resources
• work-integrated learning

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Introduction

Higher education (HE) students worldwide are increasingly engaging in paid work during study (Fényes 2021; Moreau and Leathwood 2006), motivated by financial reasons and the signalling benefits of work experience (see Hall 2010). There are conflicting perspectives on the impact of paid work (termed student employment), some purporting skill development and network building that enhances labour market appeal and employment prospects (e.g. Trolian, Jach, and Ferrell 2018), others asserting that it can distract students and negatively influence academic performance (e.g. Hall 2010). Many highlight important distinctions in the effects of student employment by hours worked and relevance to degree study (Carnevale et al. 2015; Van Belle et al. 2020) and students’ personal characteristics, such as socio-economic status (SES), citizenship and gender (e.g. Coates 2015). Relatively few studies have investigated the relationship between student employment and labour market outcomes (Fényes 2021), compared to the impact of work experience that is embedded within HE courses.

In-curriculum work experience falls under the umbrella of work-integrated learning (WIL), a suite of activities where students engage meaningfully with industry/community partners as part of their studies. Work-based WIL refers to experiences immersed in a professional setting (e.g. internships/placements/practicums/professional practice) (Jackson and Dean 2022), typically related to the field of study. There is substantial evidence of the positive influence of work-based WIL on employability outcomes, such as enhanced work readiness, connections for career purposes, and professional socialisation (e.g. Jackson 2015), academic outcomes (Johnson and Stage 2018), and positive labour market returns, including improved job attainment and reduced likelihood of job-education mismatch post-graduation (Baert et al. 2021; Carnevale et al. 2015; Nunley et al. 2017).

Although work experience is prioritised among youth employers (Kinash et al. 2016), there has been little investigation of the benefits of student employment compared to work-based WIL, and how one may influence the other (e.g. Bittmann and Zorn 2020; Jackson and Collings 2018). One might expect employed students to be less interested in work-based WIL if they felt they were already accruing the benefits of work experience. Time constraints from employment may inhibit students from choosing to participate in work-based WIL and employability-building activities beyond curriculum, such as club/society roles and volunteering (see Clark et al. 2015). This may be particularly true for less privileged students who often have greater employment obligations (Stuart et al. 2011) yet could benefit most from activities known to build cultural and social capitals for career purposes.

Insights into the relative benefits of student employment and work-based WIL are important given ongoing stakeholder pressure on HE institutions to produce work-ready graduates (Coates 2015), accentuated given the complexities of contemporary work and global talent shortages. In Australia, the government is encouraging the development of future-oriented graduates through interventions which link institutional funding to industry engagement and graduate employment outcomes (Australian Government 2019, 2020). Deepening our understanding of synergies or constraints between student employment and employability-building activities, and how this may vary among different groups, is important for optimising graduate preparedness and transition to work for increasingly diverse cohorts.

This leads to the study’s three research questions. First, how prevalent is student employment and does this vary by personal characteristics and discipline? Second, does student employment influence participation in employability-related activities and does this vary by discipline and across student groups? Third, how does student employment influence preparedness for work and graduate employment outcomes and does this change with participation in work-based WIL for different student groups? Drawing on the lens of capital resources and signalling theory, the study uses national secondary data from 152,226 recent graduates of Australian universities to address the research questions.

Background

Theoretical framework

There are several theoretical concepts which might explain why students’ work experience leads to labour market gains. Human capital theory (Becker 1964) asserts that acquiring discipline-based and professional skills, known to develop at work (Clark et al. 2015; Jackson and Bridgstock 2021), can enhance workplace performance and therefore attract labour market rewards. Yet differences in the value gained from student employment according to its relevance to the field of study (e.g. Hall 2010) contradict human capital theory which assumes positive effects from all experience, irrespective of the type of work (Weiss, Klein, and Grauenhorst 2014). Weiss and colleagues argue that signalling theory (Spence 1973), where ‘employers decide which characteristics are perceived as productive and which are not’ (p. 789), may better support interpreting how different types of student employment can accrue varied labour market gains. The authors emphasise discipline-related work experience as more clearly indicating training needs and person-job fit, thus a more reliable signal during recruitment. This is consistent with Kinash et al. (2016) who found employment perceived as unrelated to the study as less attractive to prospective employers.

It is also known that student employment can help to develop professional connections and social relationships for future career (Coates 2015; Muldoon 2009), provide important opportunities for socialisation into workplace culture (Passaretta and Triventi 2015) – including discipline-specific norms and codes (Weiss, Klein, and Grauenhorst 2014), and can improve job search effectiveness, career planning, and articulating achievements to prospective employers (Coates 2015). These learnings are particularly important for students who bring less developed social and cultural capitals into HE and therefore have more to gain from student employment (Carnevale et al. 2015). Social and cultural capital theory could therefore be important when delineating associations between student employment, work-based WIL and labour market outcomes.

Student employment and labour market outcomes

Growth in student employment has been attributed to more mature-age learners and rising costs of HE (Carnevale et al. 2015). Coates’ (2015) large-scale study of Australian HE students found at least two-thirds engage in paid work of varying hours per week, more so in later years of study, and reported higher participation rates among females, medium or high SES, domestic and metro-based students. Similarly, Hall (2010) found a steady rise in hours worked by UK students and a declining proportion of full-time students not working at all, although no apparent differences by gender. Motivations for student employment extend beyond financial gain, which is more common in low SES students, and include acquiring experience as a career enhancing strategy, even employment unrelated to study being considered important for improving skills and employment prospects (Fényes 2021).

The relationship between student employment and graduate outcomes appears complex. There are reports of both positive and negative associations with academic performance (e.g. Bartolj and Polanec 2016; McClellan, Creager, and Savoca 2018), varying by hours worked (Coates 2015), and adverse effects on attendance, belonging and retention (see Darolia 2017). Less explored is the influence on labour market outcomes, with earlier work reporting inconsistent findings (Fényes 2021). Some have observed positive relationships between student employment and full-time job attainment post-graduation (Jackson and Collings 2018; Karmel and Carroll 2016), strengthening with more hours worked (Coates and Edwards 2009), while others have reported no labour market gains (e.g. Baert et al. 2016). Although Coates and Edwards found more employed students attracted higher salaries and secured professional/managerial-level roles in the longer term, Jackson and Collings (2018) detected little employment effect on perceived overqualification among recent graduates.

The relationship between employment and field of study appears important, with some reporting labour market gains being confined to those with relevant work experience (Klein and Weiss 2011; Róbert and Saar 2012). Labour market rewards from work experience have been attributed to combinations of human capital theory (acquired skills increasing productivity and therefore marketability), cultural and social capital theory (developed networks and insights into professional culture improving access to the job market) and signalling theory (work experience sending positive signals to prospective employers) (Baert et al. 2021; Weiss, Klein, and Grauenhorst 2014).

Student employment and employability-building activities

Student employment can adversely affect participation in employability-building activities external to the curriculum given they require students to commit time and resources beyond study (Kinash et al. 2016). Kinash and colleagues highlight the range of such activities, such as volunteering, mentoring and engaging with professional associations, which may be facilitated by the university (co-curricular) or organised by students themselves (extra-curricular). Noting nuances by type, these activities are broadly considered to support student employability and improve employment prospects post-graduation by enhancing professional skills and perceived work readiness (see Jackson & Dean, 2022). They can be particularly valuable to equity groups, increasing their sense of belonging in HE and helping them to establish relationships for career purposes (e.g. Stuart et al. 2011), thus enhancing their cultural and social capitals.

Employed students having less time for work-based WIL could affect participation in optional, curriculum-based internships/placements, common to disciplines such as Information Technology and Management/Commerce (Universities Australia 2019), although earlier work has shown a strong, positive association between engagement in student employment and work-based WIL (Coates 2015). In terms of any moderating relationship between work-based WIL and student employment, Bittmann and Zorn (2020) found positive labour market effects from undertaking optional internships, irrespective of student employment. Although the authors did not attribute this to a particular reason, it could be due to WIL’s intentional design to enhance employability and prepare for future work. Campbell et al. (2019) outline how WIL should explicitly prepare students for workplace experiences, embed reflection and incorporate industry partner feedback, critical for connecting classroom learning with professional practice to optimise workplace learning and career planning (Billett 2011). Combined with optional work-based WIL signalling strong work ethic and ambition to prospective employers (see Baert et al. 2021), rich reflective activities and assessments enable students to construct meaning to support career-based learning (Hansen 2019) and clearer articulation of the value of their work experience during recruitment.

Methodology

The study draws on national secondary data gathered bi-annually online from recent graduates of HE courses in Australia. Administered by the Social Research Centre, on behalf of the Australian Government, the Graduate Outcomes Survey (GOS) focuses on learning experience, course satisfaction and the labour market destinations of Bachelor, postgraduate coursework and research graduates four-to-six months after course completion. A national summary report of GOS data is published annually, and the secondary data set is available to participating HE institutions for research and teaching and learning purposes. The national data are used by the Good University Guide (2022) to rank higher education institutions by, for example, their graduates’ job attainment rates, teaching quality and student experience.

Participants

Table 1 summarises the characteristics of the 152,226 graduates from 41 Australian universities who participated in the GOS in 2020 and 2021. Given the research questions, the sample includes only those graduates who responded to questions relating to student employment. The Bachelor sample includes those completing honours courses (coursework with thesis component).

Table 1. Participant characteristics (%).

Variable	Sub-groups	Bachelor (n = 87,338)	Postgraduate coursework (n = 56,538)	Postgraduate research (n = 8,350)	All (n = 152,226)
Age	0–24 years	72.1	24.2	2.2	50.5
	25+ years	27.9	75.8	97.8	49.5
Gender	Male	36.8	39.8	46.9	38.5
	Female	63.2	60.2	53.1	61.5
Citizenship	Domestic	83.6	62.2	64.4	74.6
	International	16.4	37.8	35.6	25.4
SES	Low	15.9	12.5	10.3	14.6
	Medium	50.9	47.2	43.4	49.5
	High	33.2	40.3	46.3	35.9
Regionality	Metro	66.6	48.2	46.7	58.6
	Regional/Remote	33.4	51.8	53.3	41.4
Mode	On-campus	71.4	61.2	94.2	68.9
	Off-campus	8.6	24.6	4.1	14.3
	Multi-mode	20.0	14.1	1.7	16.8
Attendance	Part-time	22.2	41.5	34.0	30.0
	Full-time	77.8	58.5	66.0	70.0
Discipline	Natural/Physical Science	10.9	4.0	26.2	9.2
	Information Technology	4.8	9.6	3.7	6.6
	Engineering/related	6.4	5.9	13.4	6.6
	Architecture/Building	2.7	2.6	1.1	2.6
	Agriculture/Environment	1.6	1.5	4.0	1.7
	Health	20.5	18.2	15.4	19.4
	Education	5.6	13.9	6.1	8.7
	Management/Commerce	15.9	23.7	5.5	18.2
	Society/Culture	23.2	17.9	20.4	21.1
	Creative Arts	8.4	2.7	4.2	6.1

Procedures

The response rate for the GOS was 42.3% in 2020 (n = 122,530) and 40.4% in 2021 (n = 127,827) (Social Research Centre 2020, 2021). Given these rates, the secondary data set is considered representative of the wider student population in Australia. Ethics declaration was obtained through the lead author’s institution, along with access to the national GOS data file. Graduate participant consent was provided at the time of completing the national survey. In addition to labour force-related items, the GOS collects data on five WIL/employability measures which are commissioned by the Australian Collaborative Education Network (ACEN), Australia’s professional association for WIL. Thirty universities opted to include the ACEN measures in their 2020/2021 GOS, each provided with access to their own graduates’ responses to the five items as part of their GOS institutional data file. For this study, ACEN provided access to the data generated for the five items for all 30 participating institutions. Secondary data were analysed by the research team during the first half of 2022.

With respect to the survey timing, it is important to acknowledge any potential impact from COVID-19. Lockdown restrictions were implemented in Australia at various times during 2020, depending on the state in which graduates were located. This may have affected graduates’ ability to secure and maintain employment during their studies, as well as after course completion. Reports on the GOS results (Social Research Centre 2020, 2021) indicated that graduate employment outcomes were in decline prior to the 2020 survey, worsened during 2020 and then stabilised in 2021. The SRC indicated that this pattern reflected the cycle of pandemic-related restrictions and labour market conditions in Australia. They also reported a substantial reduction in the average hours worked by graduates during the second half of 2020. This was particularly so for part-time workers, which was attributed to their greater likelihood of being in customer-facing roles affected by pandemic-related restrictions. One might surmise that this downturn trend would extend to paid work during study.

Measures

Government course-completion data are used to populate personal variables in the GOS, including mature-age (≥25 years when commencing study), gender, citizenship (domestic/international at enrolment), SES and regionality (both residential postcode). GOS labour force-related items include whether a graduate is in full-time employment (proportion of graduates working full time of those available for full-time work), and their perceptions of overqualification in their current role. The SRC uses Maynard’s (2006) eight-item Scale of Perceived Qualification (strongly disagree [1] to strongly agree [5]) to calculate a mean score for graduates with at least six valid item responses, classifying them as considering themselves over-qualified (or not). Full-time work is defined as ≥35 h/week. Further, to gauge preparedness, graduates are asked ‘overall, how well did your qualification prepare you for your job’ (‘not at all’ [1] to ‘very well’ [4], and an ‘unsure’ option). The proportion of graduates who rated ‘well’ or ‘very well’ are considered prepared.

ACEN’s five items span student employment, participation in WIL and in extra/co-curricular, employability-related activities (ERAs). For student employment, graduates select the type(s) of work they engaged in at any time during study, classified into full-time/part-time and by relevance to intended career, including a ‘none of these’ option. Graduates indicate whether they participated in work-based WIL activities (internship/work placement/practicum/professional practice) as part of their course. Finally, they indicate whether they engaged in certain extra/co-curricular (beyond formal study, self-sourced or university facilitated) ERAs: ‘position of responsibility in a club/society’, ‘industry-based mentoring arrangement’, ‘enterprise incubator/start-up activity’, ‘leadership/award program’, or ‘micro-credentialing/digital badge program’.

Analysis

Once data were accessed, the research team used SPSS 26.0 to analyse the merged sample of 2020/2021 graduate responses. Frequency counts and percentages addressed the research questions. Consistent with earlier reporting on the analysis of large data sets on student employment (e.g. Coates 2015), formal tests of significance (e.g. Pearson chi-square) are not reported given their tendency to produce significant p-values (Lin, Lucas, and Shmueli 2013). For investigation of the impact on graduate outcomes, analysis is confined to domestic graduates in full-time work, consistent with SRC’s reporting conventions. Further, parts of the analysis are confined to Bachelor graduates, clearly outlined in the results.

Results

Participation in student employment

Participation in different types of student employment is summarised in Table 2. Overall, results indicated considerable variation across course levels, commensurate with different career and life stages. Variation was most prevalent in employment relevant to intended career with more than one-quarter of coursework postgraduates participating full time compared with 10.9% and 14.4% of undergraduates and research postgraduates, respectively. One-half of research postgraduates reported participation in relevant part-time employment compared to approximately one-quarter of the coursework groups. There was also variation in non-relevant, part-time work, with almost one-half of undergraduates reporting participation, approximately double that of postgraduates. In contrast, participation in non-relevant full-time work was relatively stable, hovering at around 5% across the groups. Further, the proportion who did not engage in any form of employment was static at around one-fifth of each course cohort across the two-year period. Broadly, full-time employment was substantially less common than part-time work.

Table 2. Participation in student employment (%).

	All (n = 152,226)	Bachelor (n = 87,338)	Postgraduate coursework (n = 56,538)	Postgraduate research (n = 8,350)
Full-time relevant to intended career	17.4	10.9	27.8	14.4
Part-time relevant to intended career	27.5	28.5	22.5	5.5
Full-time not relevant to intended career	6.6	7.3	6.0	2.2
Part-time not relevant to intended career	39.7	48.8	28.6	19.4
None	19.3	18.3	2.8	2.2

A breakdown of student employment by a discipline group is presented in Table 3. The results indicate considerable variation across disciplines with proportionately more students in relevant employment in Engineering, Education, Health, Management/Commerce and Architecture/Building, particularly compared to Natural/Physical Sciences and – to a lesser extent – Creative Arts. While there were high levels of both full-time and part-time relevant employment for Engineering students, those in Architecture/Building and Management/Commerce tended to work full-time, and Health and Education part-time. A relatively high incidence of non-relevant employment – irrespective of hours – was reported for Society/Culture, Science, Agriculture/Environment and Creative Arts students. The greatest proportion of students not working at all were in IT and Science and the lowest was in Education.

Table 3. Participation in Bachelor’s student employment by discipline (%).

	All (n = 87,338)	Science (n = 10,302)	IT (n = 4,327)	Eng’ing (n = 5,817)	Arch/Bld (n = 2,331)	Agri/Env (n = 1,410)	Health (n = 18,520)	Education (n = 5,473)	Mgt/Com (n = 16,279)	Soc/Culture (n = 22,842)	C’tive Arts (n = 7,481)
Full-time relevant to intended career	10.9	4.0	15.6	19.9	17.2	9.6	5.9	11.8	18.0	10.9	6.0
Part-time relevant to intended career	28.5	18.5	24.1	34.0	26.6	28.3	39.3	43.9	26.9	26.7	26.3
Full-time not relevant to intended career	7.3	4.9	5.2	5.9	7.0	7.4	5.2	7.5	8.8	10.1	6.8
Part-time not relevant to intended career	48.8	59.4	43.5	54.3	46.1	54.9	43.5	41.5	46.8	54.5	52.3
None	18.3	22.5	26.7	16.7	19.9	15.7	14.5	11.2	18.3	16.0	20.7

Table 4 summarises participation in employment by background characteristics at course level and shows variability across groups. Gender differences appeared modest, males broadly tending to work full-time more across the courses, both non-relevant and relevant. At Bachelor level, noticeably more females participated in both types of part-time work. This held true for both postgraduate groups for relevant employment, but is not non-relevant where the reverse result was observed among coursework graduates and little difference for those undertaking research degrees. At all course levels, relatively more females were engaged in student employment compared to males. There were some consistent age effects, with mature-age graduates reporting substantially greater participation in both types of full-time work across all three course cohorts. In contrast, their younger peers engaged in more non-relevant, part-time work across all courses. While overall engagement in student employment was similar among mature-age and younger graduates within Bachelor and research cohorts, fewer younger graduates were working at the postgraduate coursework level.

Table 4. Participation in student employment by background (%).

	Gender		SES			Regionality		Citizenship		Age
Employment	Male	Female	Low	Med	High	Reg/remote	Metro	Domestic	Int’l	<25	25+
Bachelor (n = 87,338)
FT relevant	13.2	9.5	12.0	11.5	11.7	9.6	11.5	11.7	6.7	8.0	18.3
PT relevant	25.8	30.1	26.7	28.9	32.1	26.8	29.4	29.5	23.5	28.1	29.5
FT non-relevant	7.9	7.0	8.1	8.4	8.0	5.5	8.3	8.2	2.8	5.5	12.0
PT non-relevant	47.6	49.6	44.2	49.9	55.6	43.2	51.6	50.8	38.8	54.9	33.1
None	21.5	16.4	20.1	15.3	12.0	25.0	14.9	15.0	35.0	18.3	18.3
PG coursework (n = 56,538)
FT relevant	28.1	27.6	39.9	40.3	39.9	16.8	39.6	40.6	6.8	10.3	33.4
PT relevant	17.7	25.6	23.7	24.4	24.4	21.1	24.0	24.2	19.7	24.8	21.7
FT non-relevant	6.5	5.7	8.5	7.7	8.5	3.8	8.3	8.2	2.4	4.1	6.6
PT non-relevant	31.9	26.4	18.3	19.8	21.1	36.3	20.3	19.7	43.3	45.0	23.4
None	22.2	19.9	14.2	13.3	13.3	27.2	14.0	13.5	32.9	24.5	19.7
PG research (n = 8,350)
FT relevant	15.4	13.6	20.9	19.5	19.3	10.1	19.3	19.9	4.5	3.7	14.7
PT relevant	48.5	52.3	49.6	52.4	55.7	47.9	53.5	53.4	45.3	50.3	50.5
FT non-relevant	2.6	1.8	2.9	3.0	2.9	1.5	3.0	2.9	0.9	1.1	2.2
PT non-relevant	19.9	19.1	22.3	20.6	19.1	19.0	20.0	19.8	18.9	32.6	19.1
None	21.7	18.9	14.9	13.0	13.6	26.2	13.5	13.4	32.5	18.7	20.3

For SES, there was a relative uniformity for full-time work – both relevant and non-relevant – across course levels. More variability was reported for part-time work with noticeably more high SES graduates undertaking relevant part-time work among Bachelor and research cohorts, and more in non-relevant part-time work at the Bachelor level. While no engagement in work was stable for postgraduates across the three SES groups, a substantially greater proportion of low SES Bachelor graduates reported not being employed during studies. There were clear differences between regional/remote and metro-based graduates, the latter participating substantially more in all types of employment at the Bachelor level. This held for postgraduates, other than for non-relevant, part-time work with a reverse effect for coursework graduates and uniformity for those completing research degrees. There was a similar pattern for citizenship, with noticeably greater participation across all types of work for domestic graduates at all course levels, other than for non-relevant, part-time work.

Student employment and participation in employability-building activities

Table 5 shows that only around one-third of Bachelor graduates not employed during study participated in work-based WIL, less than those undertaking full-time or part-time employment, relevant or not. Those in relevant employment, particularly part-time, reported the highest participation rate in work-based WIL. This only held true for coursework postgraduates working part-time, those who employed full-time engaging less in work-based WIL than those not employed. Results were relatively uniform across different work types for research graduates with no sizeable differences in participation in work-based WIL between those employed and not.

Table 5. Participation in employability-building activities by type of student employment (%).

Employment	Work-based WIL		Leadership/award		Club/society		Volunteering		Mentoring
	No	Yes	No	Yes	No	Yes	No	Yes	No	Yes
Bachelor (n = 87,338)
FT relevant	51.5 (4,780)	48.5 (4,498)	92.2 (8,317)	7.8 (706)	77.5 (6,997)	22.5 (2,026)	60.4 (5,452)	39.6 (3,571)	89.6 (8,089)	10.4 (934)
PT relevant	41.2 (10,053)	58.8 (14,352)	91.1 (21,638)	8.9 (2,114)	73.5 (17,461)	26.5 (6,291)	48.8 (11,600)	51.2 (12,152)	89.0 (21,139)	11.0 (2,613)
FT non-relevant	61.1 (3,821)	38.9 (2,434)	94.2 (5,757)	5.8 (353)	79.8 (4,878)	20.2 (1,232)	58.0 (3,545)	42.0 (2,565)	91.8 (5,608)	8.2 (502)
PT non-relevant	54.1 (22,679)	45.9 (19,256)	92.7 (38,072)	7.3 (2,999)	75.2 (30,879)	24.8 (10,192)	49.4 (20,295)	50.6 (20,776)	91.5 (37,563)	8.5 (3,508)
None	65.9 (10,346)	34.1 (5,346)	96.8 (15,003)	3.2 (503)	85.9 (13,322)	14.1 (2,184)	64.0 (9,925)	36.0 (5,581)	95.4 (14,787)	4.6 (719)
All	54.7 (46,818)	45.3 (38,823)	94.1 (78,915)	5.9 (4,954)	79.2 (66,427)	20.8 (17,442)	55.3 (46,407)	44.7 (37,462)	92.4 (77,526)	7.6 (6,343)
PG coursework (n = 56,538)
FT relevant	75.0 (11,537)	25.0 (3,839)	96.1 (14,516)	3.9 (589)	88.2 (13,326)	11.8 (1,779)	80.7 (12,184)	19.3 (2,921)	92.6 (13,991)	7.4 (1,114)
PT relevant	52.4 (6,524)	47.6 (5,933)	94.0 (11,478)	6.0 (739)	82.1 (10,033)	17.9 (2,184)	62.4 (7,620)	37.6 (4,597)	89.2 (10,902)	10.8 (1,315)
FT non-relevant	70.8 (2,366)	29.2 (974)	94.8 (3,107)	5.2 (171)	86.0 (2,819)	14.0 (459)	69.5 (2,278)	30.5 (1,000)	91.9 (3,011)	8.1 (267)
PT non-relevant	58.0 (9,213)	42.0 (6,666)	93.0 (14,576)	7.0 (1,090)	80.8 (12,664)	19.2 (3,002)	55.3 (8,659)	44.7 (7,007)	90.2 (14,135)	9.8 (1,531)
None	67.7 (7,815)	32.3 (3,725)	97.0 (11,107)	3.0 (341)	90.0 (10,303)	10.0 (1,145)	71.5 (8,182)	28.5 (3,266)	94.8 (10,848)	5.2 (600)
All	65.0 (36,001)	35.0 (19,426)	95.5 (52,119)	4.5 (2,463)	86.3 (47,123)	13.7 (7,459)	68.8 (37,537)	31.2 (17,045)	92.5 (50,514)	7.5 (4,068)
PG research (n = 8,350)
FT relevant	90.3 (1,067)	9.7 (115)	94.4 (1,115)	5.6 (66)	81.1 (958)	18.9 (223)	71.5 (844)	28.5 (337)	92.1 (1,088)	7.9 (93)
PT relevant	89.7 (3,716)	10.3 (425)	95.5 (3,949)	4.5 (187)	72.1 (2,983)	27.9 (1,153)	60.3 (2,492)	39.7 (1,644)	93.0 (3,846)	7.0 (290)
FT non-relevant	91.2 (165)	8.8 (16)	93.4 (169)	6.6 (12)	74.0 (134)	26.0 (47)	65.7 (119)	34.3 (62)	93.9 (170)	6.1 (11)
PT non-relevant	89.8 (1,439)	10.2 (164)	95.1 (1,511)	4.9 (78)	70.7 (1,124)	29.3 (465)	53.6 (851)	46.4 (738)	91.3 (1,450)	8.7 (139)
None	92.0 (1,515)	8.0 (132)	96.9 (1,599)	3.1 (52)	83.2 (1,374)	16.8 (277)	66.5 (1,098)	33.5 (553)	94.9 (1,566)	5.1 (85)
All	90.6 (7,424)	9.4 (766)	95.9 (7,848)	4.1 (334)	76.9 (6,288)	23.1 (1,894)	63.2 (5,173)	36.8 (3,009)	93.4 (7,639)	6.6 (543)

As with WIL, Bachelor graduates not employed reported the lowest engagement levels in all four ERAs compared with those employed in any type of work. The difference in engagement for those employed, or not, were less for volunteering. As for WIL, those in part-time, relevant employment engaged the most in each activity. Although differences were more moderate for coursework postgraduates, greater engagement in ERAs among those employed held true, particularly part-time workers and more so those in non-relevant employment. The popularity of ERAs among those working was evident in research graduates, although there were mixed results for part-time versus full time and relevant versus non-relevant work groups. Across the three cohorts, those working tended to favour volunteering with between one-third and one-half taking part (depending on work status), compared with the other ERAs where participation rates were much smaller.

Table 6 presents participation in work-based WIL for the different student employment types by background group. Proportionately more regional/remote, low SES, international and younger graduates who worked in full-time employment (both types) engaged in work-based WIL for their comparative group. There were also differences for those in part-time employment, greater favouring of WIL evident among females and low SES compared to males and higher SES graduates, respectively. There were less marked differences among those not working, although noticeably more females and mature-age graduates engaged in WIL.

Table 6. Bachelor graduate participation in work-based WIL by employment and background (%).

		Gender		SES			Regionality		Citizenship		Age
	All	Male	Female	Low	Med	High	Reg/remote	Metro	Domestic	Int’l	<25	25+
FT relevant	48.5	48.4	48.4	50.1	47.7	46.0	52.7	46.7	47.3	59.4	55.0	41.2
PT relevant	58.8	54.9	60.8	60.6	60.6	55.8	60.3	58.1	58.8	58.8	58.2	60.4
FT non-relevant	38.9	37.6	39.8	42.5	38.0	37.5	41.7	38.0	38.3	48.1	41.5	35.8
PT non-relevant	45.9	42.4	47.9	48.5	47.8	44.4	45.8	46.0	46.6	41.6	45.4	48.4
None	34.1	30.0	37.2	36.1	36.3	33.4	33.2	34.8	35.4	31.1	32.8	37.3

A breakdown of participation in work-based WIL by employment type and discipline is presented in Table 7, affirming variations across discipline groups. Proportionately more students from Engineering, Health and Education undertook work-based WIL when employed, irrespective of whether it was full-time/part-time or relevant/non-relevant. Focusing on the effect of employment on participation in work-based WIL, the greatest differences were reported for Architecture/Building and, to a lesser extent, IT and Management/Commerce. Broadly, across most disciplines, the impact of being employed was positive, meaning students that worked tended to engage more in work-based WIL, and the effect was greater for relevant compared to non-relevant employment.

Table 7. Bachelor graduate participation in work-based WIL by employment and discipline (%).

	All disciplines	Science	IT	Eng	Arch/Build	Agri/Env	Health	Education	Mgmt/Commerce	Society/Culture	Creative Arts
FT relevant	48.5	43.9	42.6	75.5	58.2	51.9	69.5	73.7	38.3	37.1	42.3
PT relevant	58.8	42.4	46.5	74.8	44.2	57.4	76.5	80.5	47.0	47.9	46.5
FT non-relevant	38.9	29.9	28.5	64.0	37.0	48.5	65.5	74.9	31.3	29.1	40.3
PT non-relevant	45.9	30.8	37.6	63.8	32.3	49.7	73.3	82.8	38.6	37.4	42.8
No employment	34.1	24.9	26.4	44.6	18.1	39.2	64.6	70.5	24.5	25.7	29.6

Impact of student employment on graduate outcomes

Table 8 presents the proportion of domestic Bachelor graduates who achieved full-time employment, felt prepared for their current role, and perceived themselves as overqualified in their job against the different types of employment. As expected, those who worked full time in relevant roles achieved the highest full-time employment rate across work groups, perhaps attributed to continuing in their paid roles upon graduation. However, those who undertook part-time relevant employment reported the lowest rate of overqualification and the highest rate of preparedness for work. While non-relevant, full-time student employment created an advantage for acquiring full-time graduate roles, around one-half of this group felt overqualified in their current jobs and less than two-thirds felt prepared for work (the lowest proportion across all groups, even those who were not employed during study). In contrast, relevant employment led to lower levels of overqualification and enhanced graduates’ sense of preparedness, particularly among those working part-time. Part-time, non-relevant employment reported marginally weaker rates of preparedness and overqualification compared to those in full-time, relevant student employment yet slightly better than those unemployed. Less than one-half of those not working secured full-time roles post-graduation, the lowest of all groups.

Table 8. Impact of student employment on domestic Bachelor graduate outcomes (%) (n = 49,628).

Student employment	Full-time employment	Overqualification	Preparedness for work
FT relevant	90.5 (6,844)	26.2 (1,790)	79.3 (5,419)
PT relevant	80.3 (12,252)	19.5 (2,383)	85.1 (10,415)
FT non-relevant	79.3 (3,893)	50.6 (1,964)	59.1 (2,294)
PT non-relevant	64.9 (16,101)	29.9 (4,797)	76.4 (12,278)
None	43.3 (2,734)	32.7 (892)	71.7 (1,957)

The results for full-time employment, overqualification and preparedness by employment type were separated for those who undertook work-based WIL, and those who did not (see Table 9). In terms of full-time job attainment, participating in work-based WIL made little difference if in full-time student employment, of any type. There was a small, positive effect for those who worked part-time in relevant roles with the real value of work-based WIL evident for those in part-time, non-relevant employment or not working. In contrast, the impact of work-based WIL on overqualification and preparedness for work was consistently positive, irrespective of student employment type. The benefits of work-based WIL were felt more acutely among those not employed, or employed in non-relevant roles, with sizeable gains reported.

Table 9. Impact of student employment on domestic Bachelor graduate outcomes by participation in work-based WIL (%).

	Full-time employment		Overqualification		Preparedness for work
	No WIL	WIL	No WIL	WIL	No WIL	WIL
FT relevant	92.0 (3,903)	89.0 (3,487)	30.1 (3,586)	21.8 (3,096)	76.2 (2,731)	83.0 (2,572)
PT relevant	77.5 (5,699)	81.9 (9,280)	25.5 (4,404)	16.1 (7,588)	80.6 (3,556)	87.7 (6,665)
FT non-relevant	78.9 (2,933)	80.0 (1,869)	57.8 (2,311)	39.1 (1,492)	51.3 (1,184)	71.1 (1,061)
PT non-relevant	57.6 (11,875)	71.7 (12,554)	39.6 (6,830)	22.4 (8,985)	67.9 (4,634)	82.8 (7,440)
None	38.8 (3,734)	49.9 (2,467)	41.0 (1,446)	23.0 (1,228)	63.4 (915)	81.5 (1,002)

Table 10 shows there were no marked differences in labour market gains accrued from different employment types for those participating in work-based WIL, other than for regional graduates. This group recorded higher rates of full-time job attainment from engaging in WIL across all employment types. As with the entire Bachelor cohort, gains from work-based WIL were particularly striking for those not employed during the study.

Table 10. Impact of student employment on domestic Bachelor full-time job attainment by participation in work-based WIL and background (%).

	Male		Female		Low SES		High SES		Reg/remote		Metro
	No WIL	WIL	No WIL	WIL	No WIL	WIL	No WIL	WIL	No WIL	WIL	No WIL	WIL
FT relevant	91.0	89.1	92.8	88.9	91.0	88.9	92.0	89.6	93.5	90.8	91.6	88.5
PT relevant	79.0	83.0	76.4	81.4	79.1	82.4	78.5	82.0	81.6	84.9	76.5	81.2
FT non-relevant	78.7	77.7	79.1	81.5	78.7	79.4	79.6	80.7	82.2	83.7	78.1	79.0
PT non-relevant	57.4	71.7	57.9	71.7	55.2	69.8	60.4	72.9	59.9	75.8	57.1	70.7
None	38.1	48.9	39.5	50.6	34.2	47.5	39.7	53.7	44.8	58.3	37.4	47.3

Discussion

The findings are broadly consistent with global evidence of high levels of student employment (Carnevale et al. 2015; Passaretta and Triventi 2015). Reflective of life and career stage, there were considerable differences in paid work patterns by course level. Working full-time in relevant employment was more prevalent among coursework postgraduate students, research graduates favoured relevant part-time work, and Bachelor graduates tended towards non-relevant, part-time work, consistent with Fényes (2021) who found two-thirds of Bachelors’ employment was unrelated to the study. Consistent with earlier studies (Carnevale et al. 2015; Coates 2015; Coates and Edwards 2009), more than three-quarters of Bachelor graduates worked during the study, a greater proportion in part-time roles, and females tended to work more than males, although part-time due to engagement in domestic roles. Lower levels of employment among students in Society/Culture, Creative Arts and Science emphasise how those in less professionally oriented courses may need additional support in accessing relevant employment during study.

There were no clear employment patterns by SES across course levels although, overall, low SES worked less than their privileged peers, echoing some (e.g. Coates 2015; Coates and Edwards 2009) and contravening others (see Moreau and Leathwood 2006). This is concerning given the purported benefits of student employment for building and signalling employability (Weiss, Klein, and Grauenhorst 2014). Greater participation in relevant, part-time employment among high SES graduates may be driven by their heightened orientation for accruing valuable work experience rather than working for short-term financial gain, common to low SES students (Fényes 2021). It could also reflect superior connectedness and greater ease in securing such work, potentially perpetuating further inequalities as relevant employment is favoured by prospective employers (Carnevale et al. 2015). Regional and international graduates’ lesser participation in student employment echoes earlier work (Coates 2015; Coates and Edwards 2009), as does mature-age graduates’ greater engagement in full-time work (Carnevale et al. 2015; Markos 2018) reflective of their life and career stage.

Collectively, the findings highlight the need for universities to build student awareness of the value of employment for future career and consider ways to increase participation among certain groups. This could be through greater support of on-campus student employment (e.McClellan, Creager, and Savoca 2018) and better connecting students with potential employers and opportunities through on-campus agencies, job boards or similar. Targeted efforts to engage certain groups, such as younger and lower SES students, into more relevant work could improve their transition to work and accelerate career advancement.

Some interesting patterns emerged when investigating research question two. Student employment clearly influences Bachelor students’ decisions on undertaking work-based WIL, affirming the positive association observed by Coates (2015). Rather than less employment freeing up more time for WIL, it appeared that employed Bachelor students understood the benefits of work experience and are more actively engaged in work-based WIL activities. The high proportion of WIL participants in relevant work could be attributed to universities enabling their employed roles to count as self-sourced work-based WIL opportunities. Those in non-relevant, full-time employment reported noticeably lower participation rates, presumably due to time constraints. Rather than a lack of awareness of the value of work experience, it is important to acknowledge that those not employed may have certain factors (e.g. disability or caring commitments) which challenge or preclude them from engaging in work-based WIL.

Nuances by employment type for the different background groups are interesting. Greater participation in WIL among low SES and regional students when employed is positive, perhaps indicating growing awareness of the need to accrue work experience for career purposes, greater support into WIL among universities and industry/community partners, and/or possible relief from time constraints associated with this group (Parutis and Howson 2020). Relatively greater engagement among younger and international graduates working full time may also reflect efforts to align their paid work and WIL opportunities. Unlike research graduates, employment seems a factor in postgraduate coursework students’ decision on undertaking work-based WIL with noticeable variations by employment type, such as part-time workers choosing to engage more.

Employment commitments also seemed to impact on decisions to engage in ERAs, with unemployed Bachelor graduates participating substantially less in all activities compared to other work groups. Again, reasons may relate to a broader lack of engagement with the employability agenda or constraining personal factors. There were also noticeable variations among postgraduate cohorts where those not employed engaged noticeably less and more so compared to those in part-time roles.

Findings supported the value of student employment for preparedness (e.g. Derous and Ryan 2008) and improving labour market outcomes (e.g. Carnevale et al. 2015; Passaretta and Triventi 2015), yet there were marked differences by employment type. Consistent with Coates and Edwards (2009), full-time work was associated with higher graduate full-time job attainment rates, students perhaps remaining in their roles when transitioning from university to the labour market. Favourable outcomes were particularly evident among part-time workers, the additional free time perhaps enabling them to better absorb their degree-based learning to instil preparedness and negotiate roles that matched with their acquired skills and knowledge.

Stronger preparedness and overqualification outcomes for those who undertook relevant student employment highlight the value from connecting work and study and practically applying degree-based learning. Indeed, it is highly concerning that one-half of those in full-time, non-relevant employment felt overqualified post-graduation and less than two-thirds felt prepared for work, supporting reported negative associations between relevant work experience and skills mismatch (e.g. Nunley et al. 2017; Passaretta and Triventi 2015). Nunley et al. advocates too much unrelated employment during study can send strong negative signals to employers of lesser ability and productivity, questioning Passaretta and Triventi’s, 2015 assertion that ‘any kind of student employment increases future employability’ (p. 247). Amplifying concern is evidence that unmatched employment in the short-term can perpetuate greater difficulty with moving into relevant, graduate-level work in the longer-term (Jackson and Li 2021; Nunley et al. 2017). In accordance with Nunley and colleagues, no paid work during the study also led to less favourable labour force outcomes post-graduation, perhaps indicating personal factors that constrain ability to work.

The findings affirm the gains from work-based WIL irrespective of student employment, particularly for those not working or whose work was unrelated to degree studies (Bittmann and Zorn 2020; Nunley et al. 2017), those located in regional/remote areas and with respect to entering graduate-level roles. WIL’s reflective activities, formative and summative feedback processes and efforts to encourage the connection of professional practice with classroom learning can develop students’ human capital (Gracia 2010; Jackson and Dean 2022) and social and cultural capital (Passaretta and Triventi 2015; Weiss, Klein, and Grauenhorst 2014), enhancing labour market outcomes.

Further, WIL’s activities and assessments often draw on ePortfolios which can help students to consider and effectively signal their learning and achievements to prospective employers (Jorre de St Jorre, Boud, and Johnson 2021). This would draw support for finding ways to encourage students to deeply reflect on their employment experiences to optimise learning and benefits (Goldfinch and Hughes 2007). Such explicit support is particularly important for less privileged students who understand less about applying and mobilising capitals acquired from employability-building activities (Parutis and Howson 2020), including student employment. Engagement in optional work-based WIL is also considered to signal greater work ethic and commitment to prospective employers, generating greater labour market gains than mandatory WIL experiences (Bittmann and Zorn 2020; Weiss, Klein, and Grauenhorst 2014)

Career exploration through work-based WIL may offer those in employment the opportunity to experiment with other roles, industries and sectors, providing important insights for career planning. One might also conclude that students who opted to engage in work-based WIL are more motivated and ambitious than others, naturally leading to more positive employment outcomes (Baert et al. 2021).

Conclusions and implications

The study uses national secondary data to develop our understanding of student employment across course levels, different disciplines and diverse groups in the Australian context, and how this can affect engagement in and accrued labour market gains from employability-building activities. Data analysis showed postgraduates engaged more in employment related to study and undergraduates tending towards unrelated, part-time employment. There were reported differences by discipline and personal characteristics with females, high SES, metro-based and mature-age undergraduates engaging more in employment. Student employment featured in decisions to engage in work-based WIL and employability-building activities beyond the curriculum. Those employed tended to participate more in both, particularly if working in relevant roles and the association with work-based WIL was elevated for low SES, regional/remote, younger and international students.

There were important distinctions in the labour market effects from different types of student employment with strong support for aligning paid work with the field of study, particularly part-time, which tended to enhance work-readiness and reduce skills mismatch post-graduation. Overall, there were clear messages on the potentially damaging effects of working full time in unrelated roles or not working at all. Work-based WIL increased job attainment post-graduation only for those employed part-time or not working at all, yet all WIL participants reported greater preparedness for work and high rates of transition to degree-aligned roles, irrespective of employment type.

Consideration of these findings is important given stakeholder pressure on HE institutions to develop future-oriented graduates that can meet market demands and address global talent shortages. First, a one-size-fits-all approach to engaging students in employability-building activities to optimise labour market returns seems inappropriate. Clearly, study level, discipline, the volume and type of employment that students are engaged in, and background characteristics make a difference to choices on work-based WIL and out-of-curricular, employability-building activities. Designing and delivering WIL and ERAs in ways that allow access and positive experiences for all is critical and should feature prominently in the literature relating to developing student employability.

Second, there is a clear need for universities to find ways to encourage students, particularly undergraduates, into relevant employment, aligning their hours to personal circumstances. Building awareness and facilitating access to such work through agencies, brokering services, and virtual job boards which foster connections with local organisations seeking student talent is critical to augment work-readiness and labour market outcomes. This is particularly important for students studying more generalist degrees and younger, low SES, regional and international graduates, some already experiencing greater difficulty securing roles post-graduation (e.g. Jackson and Li 2021). Relatedly, there needs to be clear communication on the potential dangers of full-time work unrelated to study.

Third, the study highlights the value of embedding quality WIL which packages relevant work experience with rich reflection and feedback to connect discipline-based learning with workplace experiences, supporting students’ personal employability narrative and career planning. While a priority is promoting the benefits of WIL to unemployed students, or those in work unrelated to study, building awareness should extend to those in relevant roles, including full time. Encouraging these students to streamline employment through work-based WIL programmes responds to calls to better connect students’ work experience with classroom learning and future career (Stokes 2015; Trolian, Jach, and Ferrell 2018) and supports Coates’ (2015) observation that ‘institutions could be supported to develop practices that provide students with the opportunity to gain credit towards their degree for learning through work’ (p. 80).

Finally, the study highlights how the apparent gains from WIL, in complement with student employment, may help universities achieve more uniform graduate employment outcomes among diverse cohorts, potentially remediating social inequalities. Embedding inclusive work-based WIL opportunities with guidance on mobilising acquired capital resources for future careers may benefit certain groups. Encouraging those with less cultural and social capital to engage in optional work-based WIL may help them to differentiate from the graduate pool by signalling strong levels of commitment, tenacity and motivation to employers (Baert et al. 2021; Weiss, Klein, and Grauenhorst 2014).

It is important to recognise, however, that despite work-based WIL’s benefits for bridging talent shortages, it comes with challenges. It is a complex area in which quality offerings require academics to align work-based and classroom-based activities to meet prescribed learning outcomes, design assessments that can be implemented and moderated across diverse work contexts and manage challenges in engaging and sustaining industry partnerships (e.g. Department of Industry 2014), including during periods of economic downturn when skills are less in demand. WIL requires significant resourcing and whole-of-institution effort given it spans strategic partnerships, risk, governance, teaching and learning processes, and equity considerations.

This study enhances our understanding of how student employment may affect diverse groups’ engagement in employability-building activities and their success in entering quality roles post-graduation. It makes important distinctions in labour market outcomes (job attainment/perceived overqualification/preparedness for work) and extends the investigation to different course levels. Like all studies, it has limitations. First, the use of secondary data imposes constraints on what type of data is gathered. For example, ACEN’s measure of student employment does not specify at what point work was undertaken, for how long or whether the graduate was still employed in this role. The lack of detail made it difficult to decipher any effects from COVID-19. There is also no differentiation in work-based WIL by length or optionality. Second, survey data does not allow for causal explanations, and the impact of work-based WIL is likely to be contingent on quality (Nunley et al. 2017). Finally, the analysis was conducted at a national level, and there could be nuances by State or Territory.

Nevertheless, this study provides important insights and signals directions for future research. Ongoing monitoring of trends in student employment, as well as participation in work-based WIL, is important for understanding the effects of structural labour market conditions and other factors, such as COVID-19 during the 2020/2021 reporting period. Investigations into the motivations for student employment and decisions on engaging in employability-building activities among different student groups could help HE efforts to counsel students on ways to enhance employability in line with personal circumstances. Qualitative inquiry into the gains from student employment compared to work-based WIL, and other employability-building activities, could inform HE practice in guiding diverse cohorts on ways to optimise graduate outcomes. Furthermore, a more granular analysis could explore nuances for mandatory versus elective work-based WIL at the discipline level, informing practice in developing future-oriented graduates. Institutions may also wish to undertake granular analysis at the degree course level where work-based WIL offerings are known, further developing understanding on the interplay with paid employment.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article was originally published with errors, which have now been corrected in the online version. Please see Correction (http://dx.doi.org/10.1080/0309877X.2024.2318142)